Title: Investigating the causality between Monounsaturated Fatty Acids on Cardiovascular Disease
1- Number of total SNPs in exposure: 12,321,875 SNPs
2- Number of Selected SNPs exposure: 44 SNPs
3- Number of total SNPs in outcome: 9,851,867 SNPs
4- Number of common variants between exposure and outcome: 37 SNPs
5- Number of SNPs after harmonization (action=2) = 36 SNPs
6- Number of SNPs after removing HLA region with exploring in HLA Genes, Nomenclature = 36 SNPs
7- Number of SNPs after removing those that have MAF < 0.01 = 36 SNPs
8- Checking pleiotropy by PhenoScanner:
How many SNPs have been eliminated after checking the PhenoScanner website: 4 SNPs (rs115849089, rs1260326, rs429358, and rs56289821)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 21.29 22.20 24.82 29.35 27.70 81.06
How many SNPs have been eliminated with checking the weakness: 0 SNP
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| w10boa | 0DIRXV | outcome | exposure | MR Egger | 32 | 0.0092767 | 0.0035303 | 0.0134136 |
| w10boa | 0DIRXV | outcome | exposure | Weighted median | 32 | 0.0045031 | 0.0014980 | 0.0026468 |
| w10boa | 0DIRXV | outcome | exposure | Inverse variance weighted | 32 | 0.0043228 | 0.0012409 | 0.0004945 |
| w10boa | 0DIRXV | outcome | exposure | Simple mode | 32 | 0.0085288 | 0.0032231 | 0.0126736 |
| w10boa | 0DIRXV | outcome | exposure | Weighted mode | 32 | 0.0076863 | 0.0030941 | 0.0185940 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| w10boa | 0DIRXV | outcome | exposure | MR Egger | 47.16615 | 30 | 0.0239700 |
| w10boa | 0DIRXV | outcome | exposure | Inverse variance weighted | 50.67952 | 31 | 0.0143121 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| w10boa | 0DIRXV | outcome | exposure | -0.0004509 | 0.0003016 | 0.1453901 |
## $`Main MR results`
## Exposure MR Analysis Causal Estimate Sd T-stat
## 1 beta.exposure Raw 0.004322811 0.00124086 3.483722
## 2 beta.exposure Outlier-corrected NA NA NA
## P-value
## 1 0.001496903
## 2 NA
##
## $`MR-PRESSO results`
## $`MR-PRESSO results`$`Global Test`
## $`MR-PRESSO results`$`Global Test`$RSSobs
## [1] 54.70446
##
## $`MR-PRESSO results`$`Global Test`$Pvalue
## [1] 0.015
##
##
## $`MR-PRESSO results`$`Outlier Test`
## RSSobs Pvalue
## 1 8.029625e-07 0.672
## 2 1.684675e-07 1
## 3 1.924740e-07 1
## 4 1.843632e-07 1
## 5 1.225485e-07 1
## 6 2.368531e-07 1
## 7 2.508848e-07 1
## 8 1.021119e-07 1
## 9 2.426335e-07 1
## 10 1.662435e-07 1
## 11 1.308346e-06 1
## 12 5.904347e-08 1
## 13 9.220546e-07 0.576
## 14 1.009905e-07 1
## 15 6.716404e-07 1
## 16 1.390861e-07 1
## 17 7.805953e-09 1
## 18 8.297846e-07 1
## 19 6.893822e-09 1
## 20 2.248506e-07 1
## 21 1.210955e-07 1
## 22 4.142234e-11 1
## 23 2.921072e-08 1
## 24 1.885866e-08 1
## 25 7.331039e-07 1
## 26 7.803325e-06 0.096
## 27 2.196524e-07 1
## 28 4.488497e-09 1
## 29 3.509989e-08 1
## 30 9.982133e-07 1
## 31 1.658861e-07 1
## 32 2.712064e-06 0.16
##
## $`MR-PRESSO results`$`Distortion Test`
## $`MR-PRESSO results`$`Distortion Test`$`Outliers Indices`
## [1] "No significant outliers"
##
## $`MR-PRESSO results`$`Distortion Test`$`Distortion Coefficient`
## [1] NA
##
## $`MR-PRESSO results`$`Distortion Test`$Pvalue
## [1] NA
## [1] "One SNP (rs591592) were detected by MRPRESSO and excluded for further analyses"
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| w10boa | 0DIRXV | outcome | exposure | MR Egger | 31 | 0.0090637 | 0.0036205 | 0.0181807 |
| w10boa | 0DIRXV | outcome | exposure | Weighted median | 31 | 0.0047626 | 0.0015305 | 0.0018600 |
| w10boa | 0DIRXV | outcome | exposure | Inverse variance weighted | 31 | 0.0044562 | 0.0012662 | 0.0004325 |
| w10boa | 0DIRXV | outcome | exposure | Simple mode | 31 | 0.0085243 | 0.0032072 | 0.0124861 |
| w10boa | 0DIRXV | outcome | exposure | Weighted mode | 31 | 0.0076822 | 0.0030292 | 0.0166527 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| w10boa | 0DIRXV | outcome | exposure | MR Egger | 46.90949 | 29 | 0.0190151 |
| w10boa | 0DIRXV | outcome | exposure | Inverse variance weighted | 49.88295 | 30 | 0.0127539 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| w10boa | 0DIRXV | outcome | exposure | -0.0004244 | 0.000313 | 0.1856232 |
##
## Radial IVW
##
## Estimate Std.Error t value Pr(>|t|)
## Effect (Mod.2nd) 0.004329998 0.0012410857 3.488879 4.850506e-04
## Iterative 0.004329998 0.0012410857 3.488879 4.850506e-04
## Exact (FE) 0.004577654 0.0009823369 4.659964 3.162650e-06
## Exact (RE) 0.004498928 0.0013155902 3.419703 1.775749e-03
##
##
## Residual standard error: 1.265 on 31 degrees of freedom
##
## F-statistic: 12.17 on 1 and 31 DF, p-value: 0.00148
## Q-Statistic for heterogeneity: 49.61039 on 31 DF , p-value: 0.01832529
##
## No significant outliers
## Number of iterations = 2
## [1] "No significant outliers"
## [1] "One SNP (rs964184) were detected by Radial and excluded for further analyses"
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| w10boa | 0DIRXV | outcome | exposure | MR Egger | 31 | 0.0064702 | 0.0035991 | 0.0826389 |
| w10boa | 0DIRXV | outcome | exposure | Weighted median | 31 | 0.0036906 | 0.0015056 | 0.0142386 |
| w10boa | 0DIRXV | outcome | exposure | Inverse variance weighted | 31 | 0.0035168 | 0.0011925 | 0.0031864 |
| w10boa | 0DIRXV | outcome | exposure | Simple mode | 31 | 0.0083347 | 0.0031966 | 0.0140789 |
| w10boa | 0DIRXV | outcome | exposure | Weighted mode | 31 | 0.0074323 | 0.0030396 | 0.0205665 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| w10boa | 0DIRXV | outcome | exposure | MR Egger | 40.90141 | 29 | 0.0702423 |
| w10boa | 0DIRXV | outcome | exposure | Inverse variance weighted | 41.96936 | 30 | 0.0720070 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| w10boa | 0DIRXV | outcome | exposure | -0.0002607 | 0.0002996 | 0.3913518 |
In statistics, Cook’s distance or Cook’s D is a commonly used estimate of the influence of a data point when performing a least-squares regression analysis.[1] In a practical ordinary least squares analysis, Cook’s distance can be used in several ways:
1- To indicate influential data points that are particularly worth checking for validity.
2- To indicate regions of the design space where it would be good to be able to obtain more data points.
It is named after the American statistician R. Dennis Cook, who introduced the concept in 1977.
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| w10boa | 0DIRXV | outcome | exposure | MR Egger | 25 | 0.0080165 | 0.0034233 | 0.0282202 |
| w10boa | 0DIRXV | outcome | exposure | Weighted median | 25 | 0.0063587 | 0.0016061 | 0.0000752 |
| w10boa | 0DIRXV | outcome | exposure | Inverse variance weighted | 25 | 0.0050631 | 0.0011313 | 0.0000076 |
| w10boa | 0DIRXV | outcome | exposure | Simple mode | 25 | 0.0087734 | 0.0029586 | 0.0067373 |
| w10boa | 0DIRXV | outcome | exposure | Weighted mode | 25 | 0.0082151 | 0.0027323 | 0.0061073 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| w10boa | 0DIRXV | outcome | exposure | MR Egger | 17.81368 | 23 | 0.7675161 |
| w10boa | 0DIRXV | outcome | exposure | Inverse variance weighted | 18.64924 | 24 | 0.7704279 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| w10boa | 0DIRXV | outcome | exposure | -0.0002564 | 0.0002806 | 0.3701534 |
##
## Inverse-variance weighted method
## (variants uncorrelated, random-effect model)
##
## Number of Variants : 28
##
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value
## IVW 0.005 0.001 0.003, 0.007 0.000
## ------------------------------------------------------------------
## Residual standard error = 0.911
## Residual standard error is set to 1 in calculation of confidence interval when its estimate is less than 1.
## Heterogeneity test statistic (Cochran's Q) = 22.3877 on 27 degrees of freedom, (p-value = 0.7174). I^2 = 0.0%.
## Method Estimate Std Error 95% CI P-value
## Simple median 0.006 0.002 0.003 0.009 0.000
## Weighted median 0.006 0.002 0.003 0.009 0.000
## Penalized weighted median 0.006 0.002 0.004 0.009 0.000
##
## IVW 0.005 0.001 0.003 0.007 0.000
## Penalized IVW 0.005 0.001 0.003 0.007 0.000
## Robust IVW 0.005 0.001 0.003 0.007 0.000
## Penalized robust IVW 0.005 0.001 0.003 0.007 0.000
##
## MR-Egger 0.008 0.003 0.002 0.014 0.009
## (intercept) 0.000 0.000 -0.001 0.000 0.279
## Penalized MR-Egger 0.008 0.003 0.002 0.014 0.009
## (intercept) 0.000 0.000 -0.001 0.000 0.279
## Robust MR-Egger 0.008 0.003 0.001 0.015 0.019
## (intercept) 0.000 0.000 -0.001 0.000 0.355
## Penalized robust MR-Egger 0.008 0.003 0.001 0.015 0.019
## (intercept) 0.000 0.000 -0.001 0.000 0.355
| id.exposure | id.outcome | exposure | outcome | snp_r2.exposure | snp_r2.outcome | correct_causal_direction | steiger_pval |
|---|---|---|---|---|---|---|---|
| w10boa | 0DIRXV | exposure | outcome | 0.001838 | 8.94e-05 | TRUE | 0 |
## $r2_exp
## [1] 0
##
## $r2_out
## [1] 0.25
##
## $r2_exp_adj
## [1] 0
##
## $r2_out_adj
## [1] 0.25
##
## $correct_causal_direction
## [1] FALSE
##
## $steiger_test
## [1] 0
##
## $correct_causal_direction_adj
## [1] FALSE
##
## $steiger_test_adj
## [1] 0
##
## $vz
## [1] NaN
##
## $vz0
## [1] 0
##
## $vz1
## [1] NaN
##
## $sensitivity_ratio
## [1] NaN
##
## $sensitivity_plot
## $beta.hat
## [1] 0.005121877
##
## $beta.se
## [1] 0.00112464
##
## $beta.p.value
## [1] 5.257628e-06
##
## $naive.se
## [1] 0.001104662
##
## $chi.sq.test
## [1] 21.74294
## over.dispersion loss.function beta.hat beta.se
## 1 FALSE l2 0.005121877 0.001124640
## 2 FALSE huber 0.005279650 0.001156012
## 3 FALSE tukey 0.005289270 0.001156148
## 4 TRUE l2 0.005136566 0.001147648
## 5 TRUE huber 0.005278331 0.001157411
## 6 TRUE tukey 0.005289602 0.001157629
##
## Constrained maximum likelihood method (MRcML)
## Number of Variants: 28
## Results for: cML-MA-BIC
## ------------------------------------------------------------------
## Method Estimate SE Pvalue 95% CI
## cML-MA-BIC 0.005 0.001 0.000 [0.003,0.007]
## ------------------------------------------------------------------
##
## Debiased inverse-variance weighted method
## (Over.dispersion:TRUE)
##
## Number of Variants : 28
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value Condition
## dIVW 0.005 0.001 0.003, 0.007 0.000 142.585
## ------------------------------------------------------------------
##
## Mode-based method of Hartwig et al
## (weighted, delta standard errors [not assuming NOME], bandwidth factor = 1)
##
## Number of Variants : 28
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value
## MBE 0.008 0.003 0.003, 0.013 0.002
## ------------------------------------------------------------------
Title: Investigating the causality between Monounsaturated Fatty Acids on Cardiovascular Disease
1- Number of total SNPs in exposure: 12,321,875 SNPs
2- Number of Selected SNPs exposure: 44 SNPs
3- Number of total SNPs in outcome: 9,851,867 SNPs
4- Number of common variants between exposure and outcome: 36 SNPs
5- Number of SNPs after harmonization (action=2) = 35 SNPs
6- Number of SNPs after removing HLA region with exploring in HLA Genes, Nomenclature = 35 SNPs
7- Number of SNPs after removing those that have MAF < 0.01 = 35 SNPs
8- Checking pleiotropy by PhenoScanner:
How many SNPs have been eliminated after checking the PhenoScanner website: 0 SNPs
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 21.34 22.36 24.96 31.10 30.73 86.31
How many SNPs have been eliminated with checking the weakness: 0 SNP
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| Ae0Nt5 | TcYOpY | outcome | exposure | MR Egger | 35 | 0.0109733 | 0.0049384 | 0.0332498 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Weighted median | 35 | 0.0044997 | 0.0012533 | 0.0003304 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Inverse variance weighted | 35 | 0.0057876 | 0.0016046 | 0.0003098 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Simple mode | 35 | 0.0041996 | 0.0026274 | 0.1192024 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Weighted mode | 35 | 0.0065586 | 0.0020791 | 0.0033544 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| Ae0Nt5 | TcYOpY | outcome | exposure | MR Egger | 126.6698 | 33 | 0 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Inverse variance weighted | 131.3981 | 34 | 0 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| Ae0Nt5 | TcYOpY | outcome | exposure | -0.0004771 | 0.0004298 | 0.2750741 |
## $`Main MR results`
## Exposure MR Analysis Causal Estimate Sd T-stat
## 1 beta.exposure Raw 0.005787622 0.0016045628 3.606978
## 2 beta.exposure Outlier-corrected 0.004639196 0.0009916789 4.678123
## P-value
## 1 9.827571e-04
## 2 5.392219e-05
##
## $`MR-PRESSO results`
## $`MR-PRESSO results`$`Global Test`
## $`MR-PRESSO results`$`Global Test`$RSSobs
## [1] 138.0242
##
## $`MR-PRESSO results`$`Global Test`$Pvalue
## [1] "<0.001"
##
##
## $`MR-PRESSO results`$`Outlier Test`
## RSSobs Pvalue
## 1 1.521081e-07 1
## 2 5.817698e-07 1
## 3 1.009412e-06 1
## 4 2.417938e-08 1
## 5 2.405264e-07 1
## 6 6.280592e-08 1
## 7 1.860700e-07 1
## 8 3.020725e-09 1
## 9 3.419849e-07 1
## 10 3.559686e-07 1
## 11 9.105534e-08 1
## 12 6.135183e-08 1
## 13 1.624695e-07 1
## 14 6.151788e-07 1
## 15 1.221771e-06 0.105
## 16 6.157827e-08 1
## 17 1.439327e-06 <0.035
## 18 1.753513e-07 1
## 19 3.837921e-08 1
## 20 3.905884e-06 1
## 21 9.285519e-06 <0.035
## 22 2.051024e-08 1
## 23 8.867844e-06 <0.035
## 24 4.106314e-08 1
## 25 6.460918e-08 1
## 26 3.992742e-09 1
## 27 2.082157e-07 1
## 28 1.062721e-07 1
## 29 1.867962e-06 1
## 30 1.306280e-07 1
## 31 6.780487e-08 1
## 32 4.822383e-08 1
## 33 2.477448e-07 1
## 34 2.927522e-07 1
## 35 1.914666e-07 1
##
## $`MR-PRESSO results`$`Distortion Test`
## $`MR-PRESSO results`$`Distortion Test`$`Outliers Indices`
## [1] 17 21 23
##
## $`MR-PRESSO results`$`Distortion Test`$`Distortion Coefficient`
## beta.exposure
## 24.75486
##
## $`MR-PRESSO results`$`Distortion Test`$Pvalue
## [1] 0.118
## [1] "Four SNPs (rs59014134, rs75117471, rs115849089, and rs17092642) were detected by MRPRESSO and excluded for further analyses"
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| Ae0Nt5 | TcYOpY | outcome | exposure | MR Egger | 31 | 0.0104860 | 0.0054383 | 0.0636786 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Weighted median | 31 | 0.0044096 | 0.0013655 | 0.0012407 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Inverse variance weighted | 31 | 0.0056432 | 0.0017519 | 0.0012771 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Simple mode | 31 | 0.0039667 | 0.0027647 | 0.1616979 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Weighted mode | 31 | 0.0063459 | 0.0020183 | 0.0037375 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| Ae0Nt5 | TcYOpY | outcome | exposure | MR Egger | 121.6015 | 29 | 0 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Inverse variance weighted | 125.3132 | 30 | 0 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| Ae0Nt5 | TcYOpY | outcome | exposure | -0.0004444 | 0.0004723 | 0.3545535 |
##
## Radial IVW
##
## Estimate Std.Error t value Pr(>|t|)
## Effect (Mod.2nd) 0.005791559 0.0016047538 3.609002 3.073776e-04
## Iterative 0.005791559 0.0016047538 3.609002 3.073776e-04
## Exact (FE) 0.006560284 0.0008407593 7.802808 6.054467e-15
## Exact (RE) 0.005996549 0.0015560471 3.853706 4.914767e-04
##
##
## Residual standard error: 1.921 on 34 degrees of freedom
##
## F-statistic: 13.02 on 1 and 34 DF, p-value: 0.000977
## Q-Statistic for heterogeneity: 125.4644 on 34 DF , p-value: 2.088556e-12
##
## Outliers detected
## Number of iterations = 2
## SNP Q_statistic p.value
## 1 rs2642636 11.60042 6.593689e-04
## 2 rs429358 40.64017 1.830054e-10
## 3 rs56289821 30.63685 3.111276e-08
## [1] "Three SNPs (rs2642636, rs429358, and rs56289821) were detected by Radial and excluded for further analyses"
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| Ae0Nt5 | TcYOpY | outcome | exposure | MR Egger | 32 | 0.0087907 | 0.0029480 | 0.0056400 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Weighted median | 32 | 0.0045552 | 0.0012944 | 0.0004327 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Inverse variance weighted | 32 | 0.0046392 | 0.0009917 | 0.0000029 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Simple mode | 32 | 0.0028732 | 0.0029038 | 0.3300998 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Weighted mode | 32 | 0.0075955 | 0.0023215 | 0.0026235 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| Ae0Nt5 | TcYOpY | outcome | exposure | MR Egger | 39.76543 | 30 | 0.1094881 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Inverse variance weighted | 42.71531 | 31 | 0.0784330 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| Ae0Nt5 | TcYOpY | outcome | exposure | -0.0003872 | 0.0002596 | 0.1461938 |
In statistics, Cook’s distance or Cook’s D is a commonly used estimate of the influence of a data point when performing a least-squares regression analysis.[1] In a practical ordinary least squares analysis, Cook’s distance can be used in several ways:
1- To indicate influential data points that are particularly worth checking for validity.
2- To indicate regions of the design space where it would be good to be able to obtain more data points.
It is named after the American statistician R. Dennis Cook, who introduced the concept in 1977.
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| Ae0Nt5 | TcYOpY | outcome | exposure | MR Egger | 32 | 0.0087907 | 0.0029480 | 0.0056400 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Weighted median | 32 | 0.0045552 | 0.0012803 | 0.0003739 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Inverse variance weighted | 32 | 0.0046392 | 0.0009917 | 0.0000029 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Simple mode | 32 | 0.0028732 | 0.0030813 | 0.3582952 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Weighted mode | 32 | 0.0075955 | 0.0022451 | 0.0019571 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| Ae0Nt5 | TcYOpY | outcome | exposure | MR Egger | 39.76543 | 30 | 0.1094881 |
| Ae0Nt5 | TcYOpY | outcome | exposure | Inverse variance weighted | 42.71531 | 31 | 0.0784330 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| Ae0Nt5 | TcYOpY | outcome | exposure | -0.0003872 | 0.0002596 | 0.1461938 |
##
## Inverse-variance weighted method
## (variants uncorrelated, random-effect model)
##
## Number of Variants : 32
##
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value
## IVW 0.005 0.001 0.003, 0.007 0.000
## ------------------------------------------------------------------
## Residual standard error = 1.174
## Heterogeneity test statistic (Cochran's Q) = 42.7153 on 31 degrees of freedom, (p-value = 0.0784). I^2 = 27.4%.
## Method Estimate Std Error 95% CI P-value
## Simple median 0.003 0.001 0.000 0.006 0.022
## Weighted median 0.005 0.001 0.003 0.008 0.000
## Penalized weighted median 0.006 0.001 0.004 0.009 0.000
##
## IVW 0.005 0.001 0.003 0.007 0.000
## Penalized IVW 0.005 0.001 0.003 0.007 0.000
## Robust IVW 0.005 0.001 0.003 0.007 0.000
## Penalized robust IVW 0.005 0.001 0.003 0.007 0.000
##
## MR-Egger 0.009 0.003 0.003 0.015 0.003
## (intercept) 0.000 0.000 -0.001 0.000 0.136
## Penalized MR-Egger 0.009 0.003 0.003 0.015 0.003
## (intercept) 0.000 0.000 -0.001 0.000 0.136
## Robust MR-Egger 0.009 0.003 0.003 0.016 0.006
## (intercept) 0.000 0.000 -0.001 0.000 0.159
## Penalized robust MR-Egger 0.009 0.003 0.003 0.016 0.006
## (intercept) 0.000 0.000 -0.001 0.000 0.159
| id.exposure | id.outcome | exposure | outcome | snp_r2.exposure | snp_r2.outcome | correct_causal_direction | steiger_pval |
|---|---|---|---|---|---|---|---|
| Ae0Nt5 | TcYOpY | exposure | outcome | 0.0023928 | 0.0001476 | TRUE | 0 |
## $r2_exp
## [1] 0
##
## $r2_out
## [1] 0.25
##
## $r2_exp_adj
## [1] 0
##
## $r2_out_adj
## [1] 0.25
##
## $correct_causal_direction
## [1] FALSE
##
## $steiger_test
## [1] 0
##
## $correct_causal_direction_adj
## [1] FALSE
##
## $steiger_test_adj
## [1] 0
##
## $vz
## [1] NaN
##
## $vz0
## [1] 0
##
## $vz1
## [1] NaN
##
## $sensitivity_ratio
## [1] NaN
##
## $sensitivity_plot
## $beta.hat
## [1] 0.00484049
##
## $beta.se
## [1] 0.000882532
##
## $beta.p.value
## [1] 4.139957e-08
##
## $naive.se
## [1] 0.0008690899
##
## $chi.sq.test
## [1] 41.4272
## over.dispersion loss.function beta.hat beta.se
## 1 FALSE l2 0.004840490 0.0008825320
## 2 FALSE huber 0.004956247 0.0009068622
## 3 FALSE tukey 0.004999124 0.0009073923
## 4 TRUE l2 0.004789447 0.0010042786
## 5 TRUE huber 0.004852868 0.0010587245
## 6 TRUE tukey 0.004864635 0.0010644772
##
## Constrained maximum likelihood method (MRcML)
## Number of Variants: 32
## Results for: cML-MA-BIC
## ------------------------------------------------------------------
## Method Estimate SE Pvalue 95% CI
## cML-MA-BIC 0.005 0.001 0.000 [0.003,0.007]
## ------------------------------------------------------------------
##
## Debiased inverse-variance weighted method
## (Over.dispersion:TRUE)
##
## Number of Variants : 32
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value Condition
## dIVW 0.005 0.001 0.003, 0.007 0.000 174.427
## ------------------------------------------------------------------
##
## Mode-based method of Hartwig et al
## (weighted, delta standard errors [not assuming NOME], bandwidth factor = 1)
##
## Number of Variants : 32
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value
## MBE 0.008 0.002 0.003, 0.012 0.000
## ------------------------------------------------------------------
Title: Investigating the causality between Monounsaturated Fatty Acids on Cardiovascular Disease
1- Number of total SNPs in exposure: 12,321,875 SNPs
2- Number of Selected SNPs exposure: 44 SNPs
3- Number of total SNPs in outcome: 13,586,589 SNPs
4- Number of common variants between exposure and outcome: 44 SNPs
5- Number of SNPs after harmonization (action=2) = 42 SNPs
6- Number of SNPs after removing HLA region with exploring in HLA Genes, Nomenclature = 42 SNPs
7- Number of SNPs after removing those that have MAF < 0.01 = 42 SNPs
8- Checking pleiotropy by PhenoScanner:
How many SNPs have been eliminated after checking the PhenoScanner website: 4 SNPs (rs429358, rs56289821, and rs964184)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 21.29 22.20 24.82 29.35 27.70 81.06
How many SNPs have been eliminated with checking the weakness: 0 SNP
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| AyPdJL | f31Mp6 | outcome | exposure | MR Egger | 39 | 0.0050467 | 0.0044966 | 0.2689503 |
| AyPdJL | f31Mp6 | outcome | exposure | Weighted median | 39 | 0.0041414 | 0.0021303 | 0.0518906 |
| AyPdJL | f31Mp6 | outcome | exposure | Inverse variance weighted | 39 | 0.0063470 | 0.0017815 | 0.0003671 |
| AyPdJL | f31Mp6 | outcome | exposure | Simple mode | 39 | 0.0002188 | 0.0045634 | 0.9620027 |
| AyPdJL | f31Mp6 | outcome | exposure | Weighted mode | 39 | 0.0003692 | 0.0049426 | 0.9408443 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| AyPdJL | f31Mp6 | outcome | exposure | MR Egger | 73.64755 | 37 | 0.0003178 |
| AyPdJL | f31Mp6 | outcome | exposure | Inverse variance weighted | 73.84589 | 38 | 0.0004383 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| AyPdJL | f31Mp6 | outcome | exposure | 0.0001302 | 0.0004124 | 0.7540298 |
## $`Main MR results`
## Exposure MR Analysis Causal Estimate Sd T-stat
## 1 beta.exposure Raw 0.006346974 0.001781519 3.562676
## 2 beta.exposure Outlier-corrected 0.005401467 0.001630537 3.312691
## P-value
## 1 0.001008592
## 2 0.002072496
##
## $`MR-PRESSO results`
## $`MR-PRESSO results`$`Global Test`
## $`MR-PRESSO results`$`Global Test`$RSSobs
## [1] 78.32892
##
## $`MR-PRESSO results`$`Global Test`$Pvalue
## [1] "<0.001"
##
##
## $`MR-PRESSO results`$`Outlier Test`
## RSSobs Pvalue
## 1 7.589045e-09 1
## 2 1.520959e-07 1
## 3 1.195763e-05 1
## 4 1.151350e-05 <0.039
## 5 1.315259e-05 1
## 6 1.829718e-08 1
## 7 3.177484e-06 0.546
## 8 7.762960e-07 1
## 9 2.255390e-07 1
## 10 6.914358e-07 1
## 11 6.033486e-07 1
## 12 2.501580e-07 1
## 13 1.045150e-06 1
## 14 3.219794e-05 1
## 15 2.531421e-06 0.117
## 16 1.119834e-06 1
## 17 1.536286e-07 1
## 18 2.737095e-07 1
## 19 1.442225e-06 1
## 20 1.196424e-06 1
## 21 1.358017e-08 1
## 22 8.712847e-07 1
## 23 5.256833e-07 1
## 24 1.713336e-08 1
## 25 8.242892e-06 1
## 26 1.273851e-07 1
## 27 2.723757e-06 1
## 28 2.269390e-06 0.702
## 29 7.465580e-08 1
## 30 1.582110e-07 1
## 31 6.197990e-08 1
## 32 2.102623e-07 1
## 33 4.351909e-06 1
## 34 3.165556e-06 1
## 35 1.212979e-06 1
## 36 3.320494e-06 1
## 37 1.093058e-07 1
## 38 1.275663e-07 1
## 39 6.704272e-07 1
##
## $`MR-PRESSO results`$`Distortion Test`
## $`MR-PRESSO results`$`Distortion Test`$`Outliers Indices`
## [1] 4
##
## $`MR-PRESSO results`$`Distortion Test`$`Distortion Coefficient`
## beta.exposure
## 17.50465
##
## $`MR-PRESSO results`$`Distortion Test`$Pvalue
## [1] 0.471
## [1] "One SNP (rs115849089) were detected by MRPRESSO and excluded for further analyses"
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| AyPdJL | f31Mp6 | outcome | exposure | MR Egger | 38 | 0.0032148 | 0.0040745 | 0.4352741 |
| AyPdJL | f31Mp6 | outcome | exposure | Weighted median | 38 | 0.0040640 | 0.0021087 | 0.0539520 |
| AyPdJL | f31Mp6 | outcome | exposure | Inverse variance weighted | 38 | 0.0054015 | 0.0016305 | 0.0009240 |
| AyPdJL | f31Mp6 | outcome | exposure | Simple mode | 38 | 0.0003045 | 0.0045716 | 0.9472453 |
| AyPdJL | f31Mp6 | outcome | exposure | Weighted mode | 38 | 0.0004557 | 0.0052850 | 0.9317594 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| AyPdJL | f31Mp6 | outcome | exposure | MR Egger | 57.64511 | 36 | 0.0124632 |
| AyPdJL | f31Mp6 | outcome | exposure | Inverse variance weighted | 58.19616 | 37 | 0.0145811 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| AyPdJL | f31Mp6 | outcome | exposure | 0.0002176 | 0.0003709 | 0.5611136 |
##
## Radial IVW
##
## Estimate Std.Error t value Pr(>|t|)
## Effect (Mod.2nd) 0.006372348 0.001783352 3.573243 3.525878e-04
## Iterative 0.006372348 0.001783352 3.573243 3.525878e-04
## Exact (FE) 0.006807760 0.001295684 5.254183 1.486830e-07
## Exact (RE) 0.006573021 0.001994518 3.295543 2.134160e-03
##
##
## Residual standard error: 1.379 on 38 degrees of freedom
##
## F-statistic: 12.77 on 1 and 38 DF, p-value: 0.000979
## Q-Statistic for heterogeneity: 72.24359 on 38 DF , p-value: 0.000669887
##
## Outliers detected
## Number of iterations = 2
## SNP Q_statistic p.value
## 1 rs115849089 14.75908 0.0001221577
## [1] "One SNP (rs115849089) were detected by Radial and excluded for further analyses"
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| AyPdJL | f31Mp6 | outcome | exposure | MR Egger | 38 | 0.0032148 | 0.0040745 | 0.4352741 |
| AyPdJL | f31Mp6 | outcome | exposure | Weighted median | 38 | 0.0040640 | 0.0020613 | 0.0486539 |
| AyPdJL | f31Mp6 | outcome | exposure | Inverse variance weighted | 38 | 0.0054015 | 0.0016305 | 0.0009240 |
| AyPdJL | f31Mp6 | outcome | exposure | Simple mode | 38 | 0.0003045 | 0.0045575 | 0.9470827 |
| AyPdJL | f31Mp6 | outcome | exposure | Weighted mode | 38 | 0.0004557 | 0.0047734 | 0.9244664 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| AyPdJL | f31Mp6 | outcome | exposure | MR Egger | 57.64511 | 36 | 0.0124632 |
| AyPdJL | f31Mp6 | outcome | exposure | Inverse variance weighted | 58.19616 | 37 | 0.0145811 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| AyPdJL | f31Mp6 | outcome | exposure | 0.0002176 | 0.0003709 | 0.5611136 |
In statistics, Cook’s distance or Cook’s D is a commonly used estimate of the influence of a data point when performing a least-squares regression analysis.[1] In a practical ordinary least squares analysis, Cook’s distance can be used in several ways:
1- To indicate influential data points that are particularly worth checking for validity.
2- To indicate regions of the design space where it would be good to be able to obtain more data points.
It is named after the American statistician R. Dennis Cook, who introduced the concept in 1977.
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| AyPdJL | f31Mp6 | outcome | exposure | MR Egger | 36 | 0.0034307 | 0.0036092 | 0.3485341 |
| AyPdJL | f31Mp6 | outcome | exposure | Weighted median | 36 | 0.0029611 | 0.0021228 | 0.1630418 |
| AyPdJL | f31Mp6 | outcome | exposure | Inverse variance weighted | 36 | 0.0041525 | 0.0014793 | 0.0049989 |
| AyPdJL | f31Mp6 | outcome | exposure | Simple mode | 36 | 0.0000657 | 0.0046212 | 0.9887343 |
| AyPdJL | f31Mp6 | outcome | exposure | Weighted mode | 36 | 0.0002129 | 0.0050532 | 0.9666373 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| AyPdJL | f31Mp6 | outcome | exposure | MR Egger | 42.69331 | 34 | 0.1456808 |
| AyPdJL | f31Mp6 | outcome | exposure | Inverse variance weighted | 42.75402 | 35 | 0.1724731 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| AyPdJL | f31Mp6 | outcome | exposure | 7.28e-05 | 0.0003312 | 0.8272782 |
##
## Inverse-variance weighted method
## (variants uncorrelated, random-effect model)
##
## Number of Variants : 36
##
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value
## IVW 0.004 0.001 0.001, 0.007 0.005
## ------------------------------------------------------------------
## Residual standard error = 1.105
## Heterogeneity test statistic (Cochran's Q) = 42.7540 on 35 degrees of freedom, (p-value = 0.1725). I^2 = 18.1%.
## Method Estimate Std Error 95% CI P-value
## Simple median 0.002 0.002 -0.002 0.006 0.306
## Weighted median 0.004 0.002 0.000 0.008 0.070
## Penalized weighted median 0.003 0.002 -0.001 0.007 0.195
##
## IVW 0.004 0.001 0.001 0.007 0.005
## Penalized IVW 0.004 0.001 0.001 0.007 0.005
## Robust IVW 0.004 0.002 0.000 0.007 0.036
## Penalized robust IVW 0.004 0.002 0.000 0.007 0.036
##
## MR-Egger 0.003 0.004 -0.004 0.011 0.342
## (intercept) 0.000 0.000 -0.001 0.001 0.826
## Penalized MR-Egger 0.003 0.004 -0.004 0.011 0.342
## (intercept) 0.000 0.000 -0.001 0.001 0.826
## Robust MR-Egger 0.003 0.004 -0.006 0.011 0.532
## (intercept) 0.000 0.000 -0.001 0.001 0.756
## Penalized robust MR-Egger 0.003 0.004 -0.006 0.011 0.532
## (intercept) 0.000 0.000 -0.001 0.001 0.756
| id.exposure | id.outcome | exposure | outcome | snp_r2.exposure | snp_r2.outcome | correct_causal_direction | steiger_pval |
|---|---|---|---|---|---|---|---|
| AyPdJL | f31Mp6 | exposure | outcome | 0.0024037 | 0.0001059 | TRUE | 0 |
## $r2_exp
## [1] 0
##
## $r2_out
## [1] 0.25
##
## $r2_exp_adj
## [1] 0
##
## $r2_out_adj
## [1] 0.25
##
## $correct_causal_direction
## [1] FALSE
##
## $steiger_test
## [1] 0
##
## $correct_causal_direction_adj
## [1] FALSE
##
## $steiger_test_adj
## [1] 0
##
## $vz
## [1] NaN
##
## $vz0
## [1] 0
##
## $vz1
## [1] NaN
##
## $sensitivity_ratio
## [1] NaN
##
## $sensitivity_plot
## $beta.hat
## [1] 0.004338291
##
## $beta.se
## [1] 0.001395069
##
## $beta.p.value
## [1] 0.001872575
##
## $naive.se
## [1] 0.001370345
##
## $chi.sq.test
## [1] 42.34696
## over.dispersion loss.function beta.hat beta.se
## 1 FALSE l2 0.004338291 0.001395069
## 2 FALSE huber 0.003551043 0.001425995
## 3 FALSE tukey 0.003792444 0.001427516
## 4 TRUE l2 0.004144624 0.001487892
## 5 TRUE huber 0.003407176 0.001580644
## 6 TRUE tukey 0.003600889 0.001589118
##
## MR-Lasso method
##
## Number of variants : 36
## Number of valid instruments : 33
## Tuning parameter : 0.3418043
## ------------------------------------------------------------------
## Exposure Estimate Std Error 95% CI p-value
## exposure 0.002 0.001 -0.001, 0.005 0.197
## ------------------------------------------------------------------
##
## Constrained maximum likelihood method (MRcML)
## Number of Variants: 36
## Results for: cML-MA-BIC
## ------------------------------------------------------------------
## Method Estimate SE Pvalue 95% CI
## cML-MA-BIC 0.004 0.001 0.002 [0.002,0.007]
## ------------------------------------------------------------------
##
## Debiased inverse-variance weighted method
## (Over.dispersion:TRUE)
##
## Number of Variants : 36
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value Condition
## dIVW 0.004 0.002 0.001, 0.007 0.005 164.553
## ------------------------------------------------------------------
##
## Mode-based method of Hartwig et al
## (weighted, delta standard errors [not assuming NOME], bandwidth factor = 1)
##
## Number of Variants : 36
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value
## MBE 0.000 0.005 -0.010, 0.011 0.968
## ------------------------------------------------------------------
Title: Investigating the causality between Monounsaturated Fatty Acids on Cardiovascular Disease
1- Number of total SNPs in exposure: 12,321,875 SNPs
2- Number of Selected SNPs exposure: 44 SNPs
3- Number of total SNPs in outcome: 9,851,867 SNPs
4- Number of common variants between exposure and outcome: 34 SNPs
5- Number of SNPs after harmonization (action=2) = 33 SNPs
6- Number of SNPs after removing HLA region with exploring in HLA Genes, Nomenclature = 33 SNPs
7- Number of SNPs after removing those that have MAF < 0.01 = 33 SNPs
8- Checking pleiotropy by PhenoScanner:
How many SNPs have been eliminated after checking the PhenoScanner website: 4 SNPs (rs429358, rs429358, rs56289821, and rs964184)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 21.34 22.52 24.92 30.36 27.97 86.31
How many SNPs have been eliminated with checking the weakness: 0 SNP
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| R5oDLI | pjYnfY | outcome | exposure | MR Egger | 30 | 0.0047384 | 0.0034165 | 0.1764078 |
| R5oDLI | pjYnfY | outcome | exposure | Weighted median | 30 | 0.0015343 | 0.0012566 | 0.2220773 |
| R5oDLI | pjYnfY | outcome | exposure | Inverse variance weighted | 30 | 0.0017718 | 0.0009866 | 0.0725214 |
| R5oDLI | pjYnfY | outcome | exposure | Simple mode | 30 | 0.0015958 | 0.0026884 | 0.5573972 |
| R5oDLI | pjYnfY | outcome | exposure | Weighted mode | 30 | 0.0018886 | 0.0022402 | 0.4061129 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| R5oDLI | pjYnfY | outcome | exposure | MR Egger | 39.33190 | 28 | 0.0757304 |
| R5oDLI | pjYnfY | outcome | exposure | Inverse variance weighted | 40.48806 | 29 | 0.0762678 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| R5oDLI | pjYnfY | outcome | exposure | -0.0002567 | 0.000283 | 0.3720285 |
## $`Main MR results`
## Exposure MR Analysis Causal Estimate Sd T-stat
## 1 beta.exposure Raw 0.001771766 0.0009865994 1.795831
## 2 beta.exposure Outlier-corrected NA NA NA
## P-value
## 1 0.08294832
## 2 NA
##
## $`MR-PRESSO results`
## $`MR-PRESSO results`$`Global Test`
## $`MR-PRESSO results`$`Global Test`$RSSobs
## [1] 43.4608
##
## $`MR-PRESSO results`$`Global Test`$Pvalue
## [1] 0.085
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| R5oDLI | pjYnfY | outcome | exposure | MR Egger | 30 | 0.0047384 | 0.0034165 | 0.1764078 |
| R5oDLI | pjYnfY | outcome | exposure | Weighted median | 30 | 0.0015343 | 0.0012695 | 0.2268038 |
| R5oDLI | pjYnfY | outcome | exposure | Inverse variance weighted | 30 | 0.0017718 | 0.0009866 | 0.0725214 |
| R5oDLI | pjYnfY | outcome | exposure | Simple mode | 30 | 0.0015958 | 0.0026708 | 0.5548211 |
| R5oDLI | pjYnfY | outcome | exposure | Weighted mode | 30 | 0.0018886 | 0.0020249 | 0.3586752 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| R5oDLI | pjYnfY | outcome | exposure | MR Egger | 39.33190 | 28 | 0.0757304 |
| R5oDLI | pjYnfY | outcome | exposure | Inverse variance weighted | 40.48806 | 29 | 0.0762678 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| R5oDLI | pjYnfY | outcome | exposure | -0.0002567 | 0.000283 | 0.3720285 |
##
## Radial IVW
##
## Estimate Std.Error t value Pr(>|t|)
## Effect (Mod.2nd) 0.001771628 0.0009866445 1.795610 0.07255661
## Iterative 0.001771628 0.0009866445 1.795610 0.07255661
## Exact (FE) 0.001863303 0.0008373257 2.225302 0.02606098
## Exact (RE) 0.001838722 0.0010371981 1.772778 0.08677105
##
##
## Residual standard error: 1.179 on 29 degrees of freedom
##
## F-statistic: 3.22 on 1 and 29 DF, p-value: 0.083
## Q-Statistic for heterogeneity: 40.28686 on 29 DF , p-value: 0.07935495
##
## No significant outliers
## Number of iterations = 2
## [1] "No significant outliers"
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| R5oDLI | pjYnfY | outcome | exposure | MR Egger | 30 | 0.0047384 | 0.0034165 | 0.1764078 |
| R5oDLI | pjYnfY | outcome | exposure | Weighted median | 30 | 0.0015343 | 0.0012175 | 0.2075762 |
| R5oDLI | pjYnfY | outcome | exposure | Inverse variance weighted | 30 | 0.0017718 | 0.0009866 | 0.0725214 |
| R5oDLI | pjYnfY | outcome | exposure | Simple mode | 30 | 0.0015958 | 0.0026429 | 0.5506837 |
| R5oDLI | pjYnfY | outcome | exposure | Weighted mode | 30 | 0.0018886 | 0.0020965 | 0.3751116 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| R5oDLI | pjYnfY | outcome | exposure | MR Egger | 39.33190 | 28 | 0.0757304 |
| R5oDLI | pjYnfY | outcome | exposure | Inverse variance weighted | 40.48806 | 29 | 0.0762678 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| R5oDLI | pjYnfY | outcome | exposure | -0.0002567 | 0.000283 | 0.3720285 |
In statistics, Cook’s distance or Cook’s D is a commonly used estimate of the influence of a data point when performing a least-squares regression analysis.[1] In a practical ordinary least squares analysis, Cook’s distance can be used in several ways:
1- To indicate influential data points that are particularly worth checking for validity.
2- To indicate regions of the design space where it would be good to be able to obtain more data points.
It is named after the American statistician R. Dennis Cook, who introduced the concept in 1977.
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| R5oDLI | pjYnfY | outcome | exposure | MR Egger | 27 | 0.0050723 | 0.0030927 | 0.1135130 |
| R5oDLI | pjYnfY | outcome | exposure | Weighted median | 27 | 0.0013964 | 0.0013041 | 0.2842530 |
| R5oDLI | pjYnfY | outcome | exposure | Inverse variance weighted | 27 | 0.0011386 | 0.0008867 | 0.1990822 |
| R5oDLI | pjYnfY | outcome | exposure | Simple mode | 27 | 0.0014728 | 0.0025957 | 0.5753012 |
| R5oDLI | pjYnfY | outcome | exposure | Weighted mode | 27 | 0.0017779 | 0.0022230 | 0.4310874 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| R5oDLI | pjYnfY | outcome | exposure | MR Egger | 21.26795 | 25 | 0.6775772 |
| R5oDLI | pjYnfY | outcome | exposure | Inverse variance weighted | 23.03059 | 26 | 0.6312158 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| R5oDLI | pjYnfY | outcome | exposure | -0.0003332 | 0.000251 | 0.1962922 |
##
## Inverse-variance weighted method
## (variants uncorrelated, random-effect model)
##
## Number of Variants : 27
##
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value
## IVW 0.001 0.001 -0.001, 0.003 0.199
## ------------------------------------------------------------------
## Residual standard error = 0.941
## Residual standard error is set to 1 in calculation of confidence interval when its estimate is less than 1.
## Heterogeneity test statistic (Cochran's Q) = 23.0306 on 26 degrees of freedom, (p-value = 0.6312). I^2 = 0.0%.
## Method Estimate Std Error 95% CI P-value
## Simple median 0.001 0.001 -0.001 0.004 0.339
## Weighted median 0.001 0.001 -0.001 0.004 0.269
## Penalized weighted median 0.001 0.001 -0.001 0.004 0.269
##
## IVW 0.001 0.001 -0.001 0.003 0.199
## Penalized IVW 0.001 0.001 -0.001 0.003 0.199
## Robust IVW 0.001 0.001 -0.001 0.003 0.187
## Penalized robust IVW 0.001 0.001 -0.001 0.003 0.187
##
## MR-Egger 0.005 0.003 -0.001 0.011 0.101
## (intercept) 0.000 0.000 -0.001 0.000 0.184
## Penalized MR-Egger 0.005 0.003 -0.001 0.011 0.101
## (intercept) 0.000 0.000 -0.001 0.000 0.184
## Robust MR-Egger 0.005 0.002 0.001 0.010 0.029
## (intercept) 0.000 0.000 -0.001 0.000 0.096
## Penalized robust MR-Egger 0.005 0.002 0.001 0.010 0.029
## (intercept) 0.000 0.000 -0.001 0.000 0.096
| id.exposure | id.outcome | exposure | outcome | snp_r2.exposure | snp_r2.outcome | correct_causal_direction | steiger_pval |
|---|---|---|---|---|---|---|---|
| R5oDLI | pjYnfY | exposure | outcome | 0.0019071 | 4.99e-05 | TRUE | 0 |
## $r2_exp
## [1] 0
##
## $r2_out
## [1] 0.25
##
## $r2_exp_adj
## [1] 0
##
## $r2_out_adj
## [1] 0.25
##
## $correct_causal_direction
## [1] FALSE
##
## $steiger_test
## [1] 0
##
## $correct_causal_direction_adj
## [1] FALSE
##
## $steiger_test_adj
## [1] 0
##
## $vz
## [1] NaN
##
## $vz0
## [1] 0
##
## $vz1
## [1] NaN
##
## $sensitivity_ratio
## [1] NaN
##
## $sensitivity_plot
## $beta.hat
## [1] 0.001171598
##
## $beta.se
## [1] 0.0009206665
##
## $beta.p.value
## [1] 0.2031764
##
## $naive.se
## [1] 0.0009051455
##
## $chi.sq.test
## [1] 22.98271
## over.dispersion loss.function beta.hat beta.se
## 1 FALSE l2 0.001171598 0.0009206665
## 2 FALSE huber 0.001259075 0.0009449070
## 3 FALSE tukey 0.001207582 0.0009447155
## 4 TRUE l2 0.001173555 0.0009415467
## 5 TRUE huber 0.001249328 0.0009449544
## 6 TRUE tukey 0.001205204 0.0009447884
##
## MR-Lasso method
##
## Number of variants : 27
## Number of valid instruments : 27
## Tuning parameter : 0.3447026
## ------------------------------------------------------------------
## Exposure Estimate Std Error 95% CI p-value
## exposure 0.001 0.001 -0.001, 0.003 0.199
## ------------------------------------------------------------------
##
## Constrained maximum likelihood method (MRcML)
## Number of Variants: 27
## Results for: cML-MA-BIC
## ------------------------------------------------------------------
## Method Estimate SE Pvalue 95% CI
## cML-MA-BIC 0.001 0.001 0.193 [-0.001,0.003]
## ------------------------------------------------------------------
##
## Debiased inverse-variance weighted method
## (Over.dispersion:TRUE)
##
## Number of Variants : 27
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value Condition
## dIVW 0.001 0.001 -0.001, 0.003 0.200 151.059
## ------------------------------------------------------------------
##
## Mode-based method of Hartwig et al
## (weighted, delta standard errors [not assuming NOME], bandwidth factor = 1)
##
## Number of Variants : 27
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value
## MBE 0.002 0.002 -0.003, 0.006 0.424
## ------------------------------------------------------------------
Title: Investigating the causality between Monounsaturated Fatty Acids on Cardiovascular Disease
1- Number of total SNPs in exposure: 12,321,875 SNPs
2- Number of Selected SNPs exposure: 44 SNPs
3- Number of total SNPs in outcome: 9,851,867 SNPs
4- Number of common variants between exposure and outcome: 40 SNPs
5- Number of SNPs after harmonization (action=2) = 40 SNPs
6- Number of SNPs after removing HLA region with exploring in HLA Genes, Nomenclature = 40 SNPs
7- Number of SNPs after removing those that have MAF < 0.01 = 40 SNPs
8- Checking pleiotropy by PhenoScanner:
How many SNPs have been eliminated after checking the PhenoScanner website: 4 SNPs (rs1554903 and rs429358)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 21.29 22.26 24.01 30.47 28.10 86.31
How many SNPs have been eliminated with checking the weakness: 0 SNP
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| fAazZl | uqi37M | outcome | exposure | MR Egger | 37 | 0.0063402 | 0.0092623 | 0.4981580 |
| fAazZl | uqi37M | outcome | exposure | Weighted median | 37 | 0.0087999 | 0.0033911 | 0.0094601 |
| fAazZl | uqi37M | outcome | exposure | Inverse variance weighted | 37 | 0.0064439 | 0.0033897 | 0.0572976 |
| fAazZl | uqi37M | outcome | exposure | Simple mode | 37 | 0.0108348 | 0.0076165 | 0.1634740 |
| fAazZl | uqi37M | outcome | exposure | Weighted mode | 37 | 0.0102740 | 0.0060846 | 0.0999577 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| fAazZl | uqi37M | outcome | exposure | MR Egger | 86.47991 | 35 | 3.0e-06 |
| fAazZl | uqi37M | outcome | exposure | Inverse variance weighted | 86.48027 | 36 | 4.9e-06 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| fAazZl | uqi37M | outcome | exposure | 1.01e-05 | 0.000837 | 0.9904535 |
## $`Main MR results`
## Exposure MR Analysis Causal Estimate Sd T-stat
## 1 beta.exposure Raw 0.006443858 0.003389660 1.901034
## 2 beta.exposure Outlier-corrected 0.006519442 0.003024166 2.155782
## P-value
## 1 0.06532639
## 2 0.03826639
##
## $`MR-PRESSO results`
## $`MR-PRESSO results`$`Global Test`
## $`MR-PRESSO results`$`Global Test`$RSSobs
## [1] 91.98975
##
## $`MR-PRESSO results`$`Global Test`$Pvalue
## [1] "<0.001"
##
##
## $`MR-PRESSO results`$`Outlier Test`
## RSSobs Pvalue
## 1 4.490365e-08 1
## 2 1.714504e-06 1
## 3 2.638681e-06 1
## 4 4.078232e-05 1
## 5 2.091918e-08 1
## 6 9.352604e-07 1
## 7 1.025229e-06 1
## 8 5.783611e-06 0.37
## 9 9.252651e-07 1
## 10 6.287315e-05 1
## 11 3.280347e-08 1
## 12 2.601647e-07 1
## 13 8.342274e-07 1
## 14 9.509238e-07 1
## 15 4.911202e-06 1
## 16 3.216041e-06 1
## 17 2.075340e-07 1
## 18 1.944242e-07 1
## 19 3.563012e-08 1
## 20 5.965255e-08 1
## 21 4.735677e-05 0.444
## 22 8.391620e-07 1
## 23 3.322211e-06 1
## 24 2.996330e-05 1
## 25 4.582138e-08 1
## 26 3.658378e-06 1
## 27 2.282894e-06 1
## 28 2.723694e-05 <0.037
## 29 4.140334e-06 0.999
## 30 2.527450e-05 1
## 31 1.641552e-05 1
## 32 1.591477e-08 1
## 33 3.129629e-06 1
## 34 2.413713e-07 1
## 35 4.193323e-05 <0.037
## 36 3.043937e-06 1
## 37 1.444488e-05 0.481
##
## $`MR-PRESSO results`$`Distortion Test`
## $`MR-PRESSO results`$`Distortion Test`$`Outliers Indices`
## [1] 28 35
##
## $`MR-PRESSO results`$`Distortion Test`$`Distortion Coefficient`
## beta.exposure
## -1.159357
##
## $`MR-PRESSO results`$`Distortion Test`$Pvalue
## [1] 0.968
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| fAazZl | uqi37M | outcome | exposure | MR Egger | 36 | 0.0062364 | 0.0096263 | 0.5214344 |
| fAazZl | uqi37M | outcome | exposure | Weighted median | 36 | 0.0089921 | 0.0037121 | 0.0154201 |
| fAazZl | uqi37M | outcome | exposure | Inverse variance weighted | 36 | 0.0064117 | 0.0035025 | 0.0671570 |
| fAazZl | uqi37M | outcome | exposure | Simple mode | 36 | 0.0116985 | 0.0077081 | 0.1380716 |
| fAazZl | uqi37M | outcome | exposure | Weighted mode | 36 | 0.0108538 | 0.0062039 | 0.0889681 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| fAazZl | uqi37M | outcome | exposure | MR Egger | 86.47362 | 34 | 1.9e-06 |
| fAazZl | uqi37M | outcome | exposure | Inverse variance weighted | 86.47460 | 35 | 3.0e-06 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| fAazZl | uqi37M | outcome | exposure | 1.69e-05 | 0.00086 | 0.9844792 |
##
## Radial IVW
##
## Estimate Std.Error t value Pr(>|t|)
## Effect (Mod.2nd) 0.006446794 0.003390225 1.901583 0.057225701
## Iterative 0.006446794 0.003390225 1.901583 0.057225701
## Exact (FE) 0.006990333 0.002197330 3.181285 0.001466233
## Exact (RE) 0.006675048 0.003642112 1.832741 0.075122185
##
##
## Residual standard error: 1.544 on 36 degrees of freedom
##
## F-statistic: 3.62 on 1 and 36 DF, p-value: 0.0653
## Q-Statistic for heterogeneity: 85.81857 on 36 DF , p-value: 5.975782e-06
##
## Outliers detected
## Number of iterations = 2
## SNP Q_statistic p.value
## 1 rs7123454 12.7942 0.0003476959
## 2 rs8107974 13.0189 0.0003083633
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| fAazZl | uqi37M | outcome | exposure | MR Egger | 35 | 0.0082727 | 0.0082800 | 0.3250118 |
| fAazZl | uqi37M | outcome | exposure | Weighted median | 35 | 0.0088240 | 0.0035685 | 0.0134082 |
| fAazZl | uqi37M | outcome | exposure | Inverse variance weighted | 35 | 0.0065194 | 0.0030242 | 0.0311007 |
| fAazZl | uqi37M | outcome | exposure | Simple mode | 35 | 0.0108836 | 0.0072360 | 0.1417916 |
| fAazZl | uqi37M | outcome | exposure | Weighted mode | 35 | 0.0099036 | 0.0061075 | 0.1141422 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| fAazZl | uqi37M | outcome | exposure | MR Egger | 60.37413 | 33 | 0.0025134 |
| fAazZl | uqi37M | outcome | exposure | Inverse variance weighted | 60.46920 | 34 | 0.0034450 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| fAazZl | uqi37M | outcome | exposure | -0.0001673 | 0.0007338 | 0.8210859 |
In statistics, Cook’s distance or Cook’s D is a commonly used estimate of the influence of a data point when performing a least-squares regression analysis.[1] In a practical ordinary least squares analysis, Cook’s distance can be used in several ways:
1- To indicate influential data points that are particularly worth checking for validity.
2- To indicate regions of the design space where it would be good to be able to obtain more data points.
It is named after the American statistician R. Dennis Cook, who introduced the concept in 1977.
| id.exposure | id.outcome | outcome | exposure | method | nsnp | b | se | pval |
|---|---|---|---|---|---|---|---|---|
| fAazZl | uqi37M | outcome | exposure | MR Egger | 34 | 0.0026933 | 0.0082760 | 0.7469735 |
| fAazZl | uqi37M | outcome | exposure | Weighted median | 34 | 0.0082770 | 0.0035509 | 0.0197573 |
| fAazZl | uqi37M | outcome | exposure | Inverse variance weighted | 34 | 0.0048753 | 0.0029682 | 0.1004810 |
| fAazZl | uqi37M | outcome | exposure | Simple mode | 34 | 0.0107320 | 0.0068367 | 0.1260113 |
| fAazZl | uqi37M | outcome | exposure | Weighted mode | 34 | 0.0097417 | 0.0054812 | 0.0847364 |
| id.exposure | id.outcome | outcome | exposure | method | Q | Q_df | Q_pval |
|---|---|---|---|---|---|---|---|
| fAazZl | uqi37M | outcome | exposure | MR Egger | 52.74506 | 32 | 0.0119122 |
| fAazZl | uqi37M | outcome | exposure | Inverse variance weighted | 52.87712 | 33 | 0.0155079 |
| id.exposure | id.outcome | outcome | exposure | egger_intercept | se | pval |
|---|---|---|---|---|---|---|
| fAazZl | uqi37M | outcome | exposure | 0.0002031 | 0.0007175 | 0.7789617 |
##
## Inverse-variance weighted method
## (variants uncorrelated, random-effect model)
##
## Number of Variants : 34
##
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value
## IVW 0.005 0.003 -0.001, 0.011 0.100
## ------------------------------------------------------------------
## Residual standard error = 1.266
## Heterogeneity test statistic (Cochran's Q) = 52.8771 on 33 degrees of freedom, (p-value = 0.0155). I^2 = 37.6%.
## Method Estimate Std Error 95% CI P-value
## Simple median 0.008 0.004 0.001 0.015 0.030
## Weighted median 0.009 0.004 0.001 0.016 0.019
## Penalized weighted median 0.009 0.004 0.002 0.016 0.014
##
## IVW 0.005 0.003 -0.001 0.011 0.100
## Penalized IVW 0.005 0.003 -0.001 0.011 0.100
## Robust IVW 0.005 0.003 -0.001 0.011 0.090
## Penalized robust IVW 0.005 0.003 -0.001 0.011 0.090
##
## MR-Egger 0.003 0.008 -0.014 0.019 0.745
## (intercept) 0.000 0.001 -0.001 0.002 0.777
## Penalized MR-Egger 0.003 0.008 -0.014 0.019 0.745
## (intercept) 0.000 0.001 -0.001 0.002 0.777
## Robust MR-Egger 0.003 0.011 -0.018 0.024 0.775
## (intercept) 0.000 0.001 -0.002 0.002 0.836
## Penalized robust MR-Egger 0.003 0.011 -0.018 0.024 0.775
## (intercept) 0.000 0.001 -0.002 0.002 0.836
| id.exposure | id.outcome | exposure | outcome | snp_r2.exposure | snp_r2.outcome | correct_causal_direction | steiger_pval |
|---|---|---|---|---|---|---|---|
| fAazZl | uqi37M | exposure | outcome | 0.0022824 | 0.0001158 | TRUE | 0 |
## $r2_exp
## [1] 0
##
## $r2_out
## [1] 0.25
##
## $r2_exp_adj
## [1] 0
##
## $r2_out_adj
## [1] 0.25
##
## $correct_causal_direction
## [1] FALSE
##
## $steiger_test
## [1] 0
##
## $correct_causal_direction_adj
## [1] FALSE
##
## $steiger_test_adj
## [1] 0
##
## $vz
## [1] NaN
##
## $vz0
## [1] 0
##
## $vz1
## [1] NaN
##
## $sensitivity_ratio
## [1] NaN
##
## $sensitivity_plot
## $beta.hat
## [1] 0.00515672
##
## $beta.se
## [1] 0.002410337
##
## $beta.p.value
## [1] 0.03240175
##
## $naive.se
## [1] 0.002368768
##
## $chi.sq.test
## [1] 52.62634
## over.dispersion loss.function beta.hat beta.se
## 1 FALSE l2 0.005156720 0.002410337
## 2 FALSE huber 0.006313638 0.002479360
## 3 FALSE tukey 0.006002630 0.002477515
## 4 TRUE l2 0.003985094 0.003767475
## 5 TRUE huber 0.004148444 0.004721347
## 6 TRUE tukey 0.004112417 0.004479062
##
## MR-Lasso method
##
## Number of variants : 34
## Number of valid instruments : 27
## Tuning parameter : 0.3036984
## ------------------------------------------------------------------
## Exposure Estimate Std Error 95% CI p-value
## exposure 0.008 0.003 0.003, 0.013 0.003
## ------------------------------------------------------------------
##
## Constrained maximum likelihood method (MRcML)
## Number of Variants: 34
## Results for: cML-MA-BIC
## ------------------------------------------------------------------
## Method Estimate SE Pvalue 95% CI
## cML-MA-BIC 0.005 0.002 0.034 [0.000,0.010]
## ------------------------------------------------------------------
##
## Debiased inverse-variance weighted method
## (Over.dispersion:TRUE)
##
## Number of Variants : 34
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value Condition
## dIVW 0.005 0.003 -0.001, 0.011 0.098 160.809
## ------------------------------------------------------------------
##
## Mode-based method of Hartwig et al
## (weighted, delta standard errors [not assuming NOME], bandwidth factor = 1)
##
## Number of Variants : 34
## ------------------------------------------------------------------
## Method Estimate Std Error 95% CI p-value
## MBE 0.010 0.006 -0.002, 0.021 0.102
## ------------------------------------------------------------------